Late fusion of facial dynamics for automatic expression recognition

Authors

ALESSANDRA BANDRABUR
LAURA FLOREA
CORNEL FLOREA
MATEI MANCAS

DOI

10.3906/elk-1607-113

Abstract

Installment of a facial expression is associated with contractions and extensions of specific facial muscles. Noting that expression is about changes, we present a model for expression classification based on facial landmarks dynamics. Our model isolates the trajectory of facial fiducial points by wrapping them up in relevant features and discriminating among various alternatives with a machine learning classification system. The used features are geometric and temporal-based and the classification system is represented by a late fusion framework that combines several neural networks with binary responses. The proposed method is robust, being able to handle complex expression classes.

Keywords

Feature extraction, machine learning, facial expression recognition

First Page

2696

Last Page

2707

Recommended Citation

BANDRABUR, ALESSANDRA; FLOREA, LAURA; FLOREA, CORNEL; and MANCAS, MATEI (2017) "Late fusion of facial dynamics for automatic expression recognition," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 25: No. 4, Article 12. https://doi.org/10.3906/elk-1607-113
Available at: https://journals.tubitak.gov.tr/elektrik/vol25/iss4/12